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Salama H, Salama A, Oscher L, Jallo GI, Shimony N. The role of neuromodulation in the management of drug-resistant epilepsy. Neurol Sci 2024; 45:4243-4268. [PMID: 38642321 DOI: 10.1007/s10072-024-07513-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 04/02/2024] [Indexed: 04/22/2024]
Abstract
Drug-resistant epilepsy (DRE) poses significant challenges in terms of effective management and seizure control. Neuromodulation techniques have emerged as promising solutions for individuals who are unresponsive to pharmacological treatments, especially for those who are not good surgical candidates for surgical resection or laser interstitial therapy (LiTT). Currently, there are three neuromodulation techniques that are FDA-approved for the management of DRE. These include vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation (RNS). Device selection, optimal time, and DBS and RNS target selection can also be challenging. In general, the number and localizability of the epileptic foci, alongside the comorbidities manifested by the patients, substantially influence the selection process. In the past, the general axiom was that DBS and VNS can be used for generalized and localized focal seizures, while RNS is typically reserved for patients with one or two highly localized epileptic foci, especially if they are in eloquent areas of the brain. Nowadays, with the advance in our understanding of thalamic involvement in DRE, RNS is also very effective for general non-focal epilepsy. In this review, we will discuss the underlying mechanisms of action, patient selection criteria, and the evidence supporting the use of each technique. Additionally, we explore emerging technologies and novel approaches in neuromodulation, such as closed-loop systems. Moreover, we examine the challenges and limitations associated with neuromodulation therapies, including adverse effects, complications, and the need for further long-term studies. This comprehensive review aims to provide valuable insights on present and future use of neuromodulation.
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Affiliation(s)
- HusamEddin Salama
- Al-Quds University-School of Medicine, Abu Dis, Jerusalem, Palestine
| | - Ahmed Salama
- Al-Quds University-School of Medicine, Abu Dis, Jerusalem, Palestine
| | - Logan Oscher
- Department of Neurosurgery, Institute for Brain Protection Sciences, Johns Hopkins All Children's Hospital, 600 5th Street South, St. Petersburg, FL, 33701, USA
| | - George I Jallo
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.
- Department of Neurosurgery, Institute for Brain Protection Sciences, Johns Hopkins All Children's Hospital, 600 5th Street South, St. Petersburg, FL, 33701, USA.
| | - Nir Shimony
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
- Department of Surgery, St. Jude Children's Research Hospital, Memphis, TN, USA
- Le Bonheur Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA
- Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN, USA
- Semmes-Murphey Clinic, Memphis, TN, USA
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Wong GM, McCray A, Hom K, Teti S, Cohen NT, Gaillard WD, Oluigbo CO. Outcomes of stereoelectroencephalography following failed epilepsy surgery in children. Childs Nerv Syst 2024; 40:2471-2482. [PMID: 38652142 DOI: 10.1007/s00381-024-06420-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 04/17/2024] [Indexed: 04/25/2024]
Abstract
INTRODUCTION Stereoelectroencephalography (SEEG) is valuable for delineating the seizure onset zone (SOZ) in pharmacoresistant epilepsy when non-invasive presurgical techniques are inconclusive. Secondary epilepsy surgery after initial failure is challenging and there is limited research on SEEG following failed epilepsy surgery in children. OBJECTIVE The objective of this manuscript is to present the outcomes of children who underwent SEEG after failed epilepsy surgery. METHODS In this single-institution retrospective study, demographics, previous surgery data, SEEG characteristics, management, and follow-up were analyzed for pediatric patients who underwent SEEG after unsuccessful epilepsy surgery between August 2016 and February 2023. RESULTS Fifty three patients underwent SEEG investigation during this period. Of this, 13 patients were identified who had unsuccessful initial epilepsy surgery (24%). Of these 13 patients, six patients (46%) experienced unsuccessful resective epilepsy surgery that targeted the temporal lobe, six patients (46%) underwent surgery involving the frontal lobe, and one patient (8%) had laser interstitial thermal therapy (LITT) of the right insula. SEEG in two thirds of patients (4/6) with initial failed temporal resections revealed expanded SOZ to include the insula. All 13 patients (100%) had a subsequent surgery after SEEG which was either LITT (54%) or surgical resection (46%). After the subsequent surgery, a favorable outcome (Engel class I/II) was achieved by eight patients (62%), while five patients experienced an unfavorable outcome (Engel class III/IV, 38%). Of the six patients with secondary surgical resection, four patients (67%) had favorable outcomes, while of the seven patients with LITT, two patients (29%) had favorable outcomes (Engel I/II). Average follow-up after the subsequent surgery was 37 months ±23 months. CONCLUSION SEEG following initial failed resective epilepsy surgery may help guide next steps at identifying residual epileptogenic cortex and is associated with favorable seizure control outcomes.
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Affiliation(s)
- Georgia M Wong
- Department of Neurological Surgery, Georgetown University School of Medicine, Washington, DC, USA.
| | - Ashley McCray
- Department of Neurosurgery, Children's National Hospital, Washington, DC, 20012, USA
| | - Kara Hom
- Department of Neurology, George Washington University School of Medicine, Washington, DC, USA
| | - Saige Teti
- Department of Neurosurgery, Children's National Hospital, Washington, DC, 20012, USA
| | - Nathan T Cohen
- Department of Neurology, George Washington University School of Medicine, Washington, DC, USA
- Department of Neurology, Children's National Hospital, Washington, DC, USA
| | - William D Gaillard
- Department of Neurology, George Washington University School of Medicine, Washington, DC, USA
- Department of Neurology, Children's National Hospital, Washington, DC, USA
| | - Chima O Oluigbo
- Department of Neurosurgery, Children's National Hospital, Washington, DC, 20012, USA.
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Cui CK, Wong WK, Wong CH, Gill D, Fong MWK. Case Report: Focal, generalized, or both: does generalized network involvement preclude successful epilepsy surgery? FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1425329. [PMID: 39055857 PMCID: PMC11269090 DOI: 10.3389/fnetp.2024.1425329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024]
Abstract
We present two cases with focal seizures where scalp electroencephalography (EEG) had prominent features of a developmental and epileptic encephalopathy (DEE): Case 1: a 17-year-old male with complex motor seizures whose EEG demonstrated a slow spike-and-wave pattern and generalized paroxysmal fast activity (GPFA). Case 2: a 12-year-old male with startle-induced asymmetric tonic seizures whose EEG also had a slow spike-and-wave pattern. Both patients had intracranial EEG assessment, and focal cortical resections resulted in long-term seizure freedom and resolution of generalized findings. These cases exemplify patients with focal epilepsy with networks that share similarities to generalized epilepsies, and importantly, these features did not preclude curative epilepsy surgery.
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Affiliation(s)
- Cathy K. Cui
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
| | - Wui-Kwan Wong
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
| | - Chong H. Wong
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
| | - Deepak Gill
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
| | - Michael W. K. Fong
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
- Department of Neurology, Comprehensive Epilepsy Center, Yale University School of Medicine, New Haven, CT, United States
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Gong R, Roth RW, Chang AJ, Sinha N, Parashos A, Davis KA, Kuzniecky R, Bonilha L, Gleichgerrcht E. EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes. Neurology 2024; 102:e209451. [PMID: 38820468 DOI: 10.1212/wnl.0000000000209451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties. METHODS We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time. RESULTS Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes. DISCUSSION Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.
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Affiliation(s)
- Ruxue Gong
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Rebecca W Roth
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Allen J Chang
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Nishant Sinha
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Alexandra Parashos
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Kathryn A Davis
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Ruben Kuzniecky
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Leonardo Bonilha
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
| | - Ezequiel Gleichgerrcht
- From the Department of Neurology (R.G., R.W.R., E.G.), School of Medicine, Emory University, Atlanta, GA; Department of Neurology (A.J.C., A.P.), Medical University of South Carolina, Charleston; Department of Neurology (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Department of Neurology (R.K.), Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY; and Department of Neurology (L.B.), School of Medicine, University of South Carolina, Columbia
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Widdess-Walsh P. Resting But Not Idle: Insights Into Epilepsy Network Suppression From Intracranial EEG. Epilepsy Curr 2024; 24:25-27. [PMID: 38327528 PMCID: PMC10846507 DOI: 10.1177/15357597231213247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
The Interictal Suppression Hypothesis in Focal Epilepsy: Network-Level Supporting Evidence Johnson GW, Doss DJ, Morgan VL, Paulo DL, Cai LY, Shless JS, Negi AS, Gummadavelli A, Kang H, Reddy SB, Naftel RP, Bick SK, Williams Roberson S, Dawant BM, Wallace MT, Englot DJ. Brain . 2023;146(7):2828-2845. doi:10.1093/brain/awad016 Why are people with focal epilepsy not continuously having seizures? Previous neuronal signalling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure-onset zones have increased inward connectivity that could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure-onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug-resistant focal epilepsy undergoing presurgical evaluation. We used intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation and non-involved zones. We then used diffusion imaging to acquire estimates of white-matter connectivity to evaluate structure–function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure-onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inwards connectivity and decreased outwards connectivity using both resting-state (one-way ANOVA, P -value = 3.13 × 10−13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, P -value = 2.5 × 10−3). When controlling for the distance between regions, the difference between inwards and outwards connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect P -value of 2.6 × 10−12). Structure–function coupling analyses revealed that seizure-onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect P -value of 9.76 × 10−21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0 ± 2.2% to classify early propagation and seizure-onset zones. These results suggest that seizure-onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure-onset zones. These findings have implications for the identification of seizure-onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug-resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative and neuromodulation approaches to improve surgical success rates in those suffering from drug-resistant focal epilepsy.
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Duma GM, Pellegrino G, Rabuffo G, Danieli A, Antoniazzi L, Vitale V, Scotto Opipari R, Bonanni P, Sorrentino P. Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study. Brain Commun 2023; 6:fcad348. [PMID: 38162897 PMCID: PMC10754317 DOI: 10.1093/braincomms/fcad348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/11/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Giovanni Pellegrino
- Epilepsy Program, Schulich School of Medicine and Dentistry, Western University, London N6A5C1, Canada
| | - Giovanni Rabuffo
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Lisa Antoniazzi
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza 36100, Italy
| | | | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
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Wang J, Liu Y, Wu Y, Yang K, Yang K, Yan L, Feng L. Anti-inflammatory effects of icariin in the acute and chronic phases of the mouse pilocarpine model of epilepsy. Eur J Pharmacol 2023; 960:176141. [PMID: 37866741 DOI: 10.1016/j.ejphar.2023.176141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 10/11/2023] [Accepted: 10/19/2023] [Indexed: 10/24/2023]
Abstract
Neuroinflammation mediated by microglia made a significant contribution in the pathophysiology of epilepsy. Icariin (ICA), a bioactive ingredient isolated from Epimedium, has been shown to present both antioxidant and anti-inflammatory properties. This study was to explore the potential therapeutic effects of icariin on mouse pilocarpine model of epilepsy and its underlying mechanisms in vivo and in vitro. To this end, we firstly measured the serum concentrations of the proinflammatory cytokines IL-1β and IL-6 from patients with temporal lobe epilepsy and found that patients with a higher seizure frequency showed correspondingly higher inflammatory reaction. Mouse pharmacokinetic study, transmembrane transportation assay, and cell viability assay collectively demonstrated that ICA was able to cross the blood-brain barrier and has good biocompatibility. The acute and chronic epilepsy models were next established in a pilocarpine mouse model of acquired epilepsy. Icariin has been identified that it could cross the blood-brain barrier and enter the hippocampus to exhibit therapeutic effects. ICA treatment dramatically promoted microglial polarization to the M2 phenotype in epilepsy mice both in the acute and chronic phases. Reduced release of M1-associated proinflammatory factors, such as IL-1β and IL-6, corroborates the altered glial cell polarization. Furthermore, ICA alleviated seizure intensity and mortality in acute phase epileptic mice. Models in the chronic group also showed improved general condition, cognition ability, and memory function after ICA treatment. Taken together, our research strongly suggested that icariin has the potential to treat epilepsy via inhibiting neuroinflammation by promoting microglial polarization to the M2 phenotype.
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Affiliation(s)
- Jing Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, 410008, China
| | - Yunyi Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, 410008, China; Xiangya School of Medicine, Central South University, Changsha, Hunan, 410013, China
| | - Yuanxia Wu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, 410008, China; Department of Neurology, Guizhou Provincial People's Hospital, Guiyang, Guizhou 550002, China
| | - Ke Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, 410008, China
| | - Kaiyi Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, 410008, China
| | - Luzhe Yan
- Xiangya School of Medicine, Central South University, Changsha, Hunan, 410013, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, 410008, China; Department of Neurology, Xiangya Hospital, Central South University (Jiangxi Branch), Nanchang, Jiangxi, 330000, China.
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Withers CP, Diamond JM, Yang B, Snyder K, Abdollahi S, Sarlls J, Chapeton JI, Theodore WH, Zaghloul KA, Inati SK. Identifying sources of human interictal discharges with travelling wave and white matter propagation. Brain 2023; 146:5168-5181. [PMID: 37527460 PMCID: PMC11046055 DOI: 10.1093/brain/awad259] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/30/2023] [Accepted: 07/19/2023] [Indexed: 08/03/2023] Open
Abstract
Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.
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Affiliation(s)
- C Price Withers
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joshua M Diamond
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Braden Yang
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kathryn Snyder
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shervin Abdollahi
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joelle Sarlls
- NIH MRI Research Facility, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio I Chapeton
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - William H Theodore
- Clinical Epilepsy Section, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kareem A Zaghloul
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sara K Inati
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
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Arévalo-Astrada MA, Suller-Marti A, McLachlan RS, Paredes-Aragón E, Jones ML, Parrent AG, Mirsattari SM, Lau JC, Steven DA, Burneo JG. Involvement of the posterior cingulate gyrus in temporal lobe epilepsy: A study using stereo-EEG. Epilepsy Res 2023; 198:107237. [PMID: 37890266 DOI: 10.1016/j.eplepsyres.2023.107237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 08/22/2023] [Accepted: 10/08/2023] [Indexed: 10/29/2023]
Abstract
OBJECTIVE To analyze the involvement of the posterior cingulate gyrus (PCG) during mesial temporal lobe seizures (MTLS). METHODS We retrospectively reviewed the stereo-EEG (SEEG) recordings of patients with MTLS performed in our institution from February 2013 to December 2020. Only patients who had electrode implantation in the PCG were included. Patients with lesions that could potentially alter the seizure spread pathways were excluded. We assessed the propagation patterns of MTLS with respect to the different structures sampled. RESULTS Nine of 97 patients who had at least one seizure originating in the mesial temporal region met the inclusion criteria. A total of 174 seizures were analyzed. The PCG was the first site of propagation in most of the cases (8/9 patients and 77.5% of seizures, and 7/8 patients and 65.6% of seizures after excluding an outlier patient). The fastest propagation times were towards the contralateral mesial temporal region and ipsilateral PCG. Seven patients underwent standard anterior temporal lobectomy and, of these, all but one were Engel 1 at last follow up. CONCLUSION We found the PCG to be the first propagation site of MTLS in this group of patients. These results outline the relevance of the PCG in SEEG planning strategies. Further investigations are needed to corroborate whether fast propagation to the PCG predicts a good surgical outcome.
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Affiliation(s)
- Miguel A Arévalo-Astrada
- Division of Neurology, Department of Medicine, Ottawa Hospital Research Institute, University of Ottawa, 501 Smyth Box 511, Ottawa, Ontario K1H 8L6, Canada
| | - Ana Suller-Marti
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada; Department of Paediatrics, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Richard S McLachlan
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Elma Paredes-Aragón
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Michelle-Lee Jones
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Andrew G Parrent
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Seyed M Mirsattari
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Jonathan C Lau
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - David A Steven
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada; Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada
| | - Jorge G Burneo
- Epilepsy Program, Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada; Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada; Neuro-Epidemiology Unit, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Rd. London, Ontario N6A 5A5, Canada.
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10
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Owens MR, Sather M, Fisher TL. Clinical outcomes following responsive neurostimulation implantation: a single center experience. Front Neurol 2023; 14:1240380. [PMID: 37808482 PMCID: PMC10557254 DOI: 10.3389/fneur.2023.1240380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 08/31/2023] [Indexed: 10/10/2023] Open
Abstract
Background Responsive neurostimulation (RNS) is an implantable device for persons with medically refractory focal-onset epilepsy. We report a single-center experience for RNS outcomes with special focus on stereoelectroencephalography (sEEG) for seizure onset localization. Methods We performed retrospective review of patients with drug resistant focal epilepsy implanted with the RNS System for a minimum of six months between July 2014 and July 2019. Records were reviewed for demographic data, epilepsy duration, seizure frequency, number of prior antiepileptic drugs (AEDs), number of AEDs at RNS System implantation, prior epilepsy surgery or device use, previous seizure localization with sEEG, and RNS system information. Clinical response was defined as a 50% reduction in seizures. Differing response rates were calculated using Fisher Exact test. Results 30 patients met inclusion criteria. Seventeen (57%) underwent previous sEEG. Average clinical follow up was 3.0 years. Overall response rate was 70%. Median seizure reduction was 74.5%. Response rate was 82.3% for patients with sEEG compared to 53.8% without (p = 0.08); 37.5% for prior epilepsy surgery compared to 81.8% without (p = 0.02); 70% for mesial temporal onset; 50% for previous vagal nerve stimulator compared to 77.3% without (p = 0.13). Conclusion Our response rates match or surpass outcome metrics of previous studies. Although limited by small study size, subpopulation analyses show positive response rates in patients with previous sEEG versus no sEEG and in temporal versus extratemporal pathology. Additional research is needed to evaluate efficacy of RNS in patients with previous epilepsy surgery, and utility of sEEG in this population.
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Affiliation(s)
| | | | - Tiffany L. Fisher
- Department of Neurology, Penn State Health Milton S. Hershey Medical Center, Hershey, PA, United States
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11
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Pattnaik AR, Ghosn NJ, Ong IZ, Revell AY, Ojemann WKS, Scheid BH, Georgostathi G, Bernabei JM, Conrad EC, Sinha SR, Davis KA, Sinha N, Litt B. The seizure severity score: a quantitative tool for comparing seizures and their response to therapy. J Neural Eng 2023; 20:10.1088/1741-2552/aceca1. [PMID: 37531949 PMCID: PMC11250994 DOI: 10.1088/1741-2552/aceca1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/01/2023] [Indexed: 08/04/2023]
Abstract
Objective.Epilepsy is a neurological disorder characterized by recurrent seizures which vary widely in severity, from clinically silent to prolonged convulsions. Measuring severity is crucial for guiding therapy, particularly when complete control is not possible. Seizure diaries, the current standard for guiding therapy, are insensitive to the duration of events or the propagation of seizure activity across the brain. We present a quantitative seizure severity score that incorporates electroencephalography (EEG) and clinical data and demonstrate how it can guide epilepsy therapies.Approach.We collected intracranial EEG and clinical semiology data from 54 epilepsy patients who had 256 seizures during invasive, in-hospital presurgical evaluation. We applied an absolute slope algorithm to EEG recordings to identify seizing channels. From this data, we developed a seizure severity score that combines seizure duration, spread, and semiology using non-negative matrix factorization. For validation, we assessed its correlation with independent measures of epilepsy burden: seizure types, epilepsy duration, a pharmacokinetic model of medication load, and response to epilepsy surgery. We investigated the association between the seizure severity score and preictal network features.Main results.The seizure severity score augmented clinical classification by objectively delineating seizure duration and spread from recordings in available electrodes. Lower preictal medication loads were associated with higher seizure severity scores (p= 0.018, 97.5% confidence interval = [-1.242, -0.116]) and lower pre-surgical severity was associated with better surgical outcome (p= 0.042). In 85% of patients with multiple seizure types, greater preictal change from baseline was associated with higher severity.Significance.We present a quantitative measure of seizure severity that includes EEG and clinical features, validated on gold standard in-patient recordings. We provide a framework for extending our tool's utility to ambulatory EEG devices, for linking it to seizure semiology measured by wearable sensors, and as a tool to advance data-driven epilepsy care.
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Affiliation(s)
- Akash R Pattnaik
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Nina J Ghosn
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Ian Z Ong
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Andrew Y Revell
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - William K S Ojemann
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Brittany H Scheid
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Georgia Georgostathi
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - John M Bernabei
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Erin C Conrad
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Saurabh R Sinha
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Nishant Sinha
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- These authors contributed equally to this work
| | - Brian Litt
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- These authors contributed equally to this work
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12
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Joshi S, Stephens E, Bleasel A, Bartley M, Wijayath M, Rahman Z, Varikatt W, Dexter M, Wong C. Successful stereoelectroencephalography re-evaluation in epilepsy patients after failed initial subdural grid evaluation. Epileptic Disord 2023; 25:534-544. [PMID: 37265017 DOI: 10.1002/epd2.20084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 05/19/2023] [Accepted: 05/27/2023] [Indexed: 06/03/2023]
Abstract
OBJECTIVE Epilepsy surgery success is dependent on accurate localization of the epileptogenic zone. Despite the use of invasive EEG using subdural grids and strips, surgical failures can occur. In this series, we explore the utility of a second evaluation with stereoelectroencephalography in patients whose initial invasive evaluation with subdural grid electrodes was unsuccessful in localizing seizure origin. METHODS We conducted a retrospective review of patients who underwent subdural grid evaluation (SDE) at our center and identified patients who underwent a re-evaluation with stereoelectroencephalography (SEEG). RESULTS We identified three patients who had both subdural and SEEG electrodes in the region of the identified epileptogenic zone in whom the initial SDE evaluation failed to make the patients seizure-free. Two of these patients underwent a second resection and became seizure-free. SIGNIFICANCE Stereoelectroencephalography can be useful in the re-evaluation and re-operation of patients who previously had surgical failure using SDE.
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Affiliation(s)
- Stuti Joshi
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
| | - Eleanor Stephens
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
| | - Andrew Bleasel
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Melissa Bartley
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
| | - Manori Wijayath
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Zebunnessa Rahman
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Winny Varikatt
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
- Anatomical Pathology, Westmead Hospital, Westmead, New South Wales, Australia
| | - Mark Dexter
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Chong Wong
- Department of Neurology and Neurosurgery, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
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13
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Gallagher RS, Sinha N, Pattnaik AR, Ojemann WK, Lucas A, LaRocque JJ, Bernabei JM, Greenblatt AS, Sweeney EM, Chen HI, Davis KA, Conrad EC, Litt B. Quantifying interictal intracranial EEG to predict focal epilepsy. ARXIV 2023:arXiv:2307.15170v1. [PMID: 37547655 PMCID: PMC10402195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Introduction Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials. Methods We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the "5 Sense Score (5SS)," a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians' choice of therapeutic intervention and the patient outcome. Results The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information. Conclusions Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.
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Affiliation(s)
- Ryan S Gallagher
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Perelman School of Medicine, University of Pennsylvania
| | - Nishant Sinha
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - Akash R. Pattnaik
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
| | - William K.S. Ojemann
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
| | - Alfredo Lucas
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Perelman School of Medicine, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
| | - Joshua J. LaRocque
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - John M Bernabei
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Perelman School of Medicine, University of Pennsylvania
- Department of Bioengineering, University of Pennsylvania
| | | | - Elizabeth M Sweeney
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania
| | - H Isaac Chen
- Department of Neurosurgery, University of Pennsylvania
- Corporal Michael J. Crescenz Veterans Affairs Medical Center
| | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - Erin C Conrad
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - Brian Litt
- Center for Neuroengineering and Therapeutics, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
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14
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Johnson GW, Doss DJ, Morgan VL, Paulo DL, Cai LY, Shless JS, Negi AS, Gummadavelli A, Kang H, Reddy SB, Naftel RP, Bick SK, Williams Roberson S, Dawant BM, Wallace MT, Englot DJ. The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence. Brain 2023; 146:2828-2845. [PMID: 36722219 PMCID: PMC10316780 DOI: 10.1093/brain/awad016] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/24/2022] [Accepted: 01/08/2023] [Indexed: 02/02/2023] Open
Abstract
Why are people with focal epilepsy not continuously having seizures? Previous neuronal signalling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure-onset zones have increased inward connectivity that could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure-onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug-resistant focal epilepsy undergoing presurgical evaluation. We used intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation and non-involved zones. We then used diffusion imaging to acquire estimates of white-matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure-onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inwards connectivity and decreased outwards connectivity using both resting-state (one-way ANOVA, P-value = 3.13 × 10-13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, P-value = 2.5 × 10-3). When controlling for the distance between regions, the difference between inwards and outwards connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect P-value of 2.6 × 10-12). Structure-function coupling analyses revealed that seizure-onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect P-value of 9.76 × 10-21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0 ± 2.2% to classify early propagation and seizure-onset zones. These results suggest that seizure-onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure-onset zones. These findings have implications for the identification of seizure-onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug-resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative and neuromodulation approaches to improve surgical success rates in those suffering from drug-resistant focal epilepsy.
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Affiliation(s)
- Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Jared S Shless
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Aarushi S Negi
- Department of Neuroscience, Vanderbilt University, Nashville, TN 37232, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA
| | - Shilpa B Reddy
- Department of Pediatrics, Vanderbilt Children’s Hospital, Nashville, TN 37232, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Mark T Wallace
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychology, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
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15
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Medina-Pizarro M, Spencer DD, Damisah EC. Recent advances in epilepsy surgery. Curr Opin Neurol 2023; 36:95-101. [PMID: 36762633 DOI: 10.1097/wco.0000000000001134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
PURPOSE OF REVIEW Technological innovations in the preoperative evaluation, surgical techniques and outcome prediction in epilepsy surgery have grown exponentially over the last decade. This review highlights and emphasizes relevant updates in techniques and diagnostic tools, discussing their context within standard practice at comprehensive epilepsy centres. RECENT FINDINGS High-resolution structural imaging has set an unprecedented opportunity to detect previously unrecognized subtle abnormalities. Machine learning and computer science are impacting the methodologies to analyse presurgical and surgical outcome data, building more accurate prediction models to tailor treatment strategies. Robotic-assisted placement of depth electrodes has increased the safety and ability to sample epileptogenic nodes within deep structures, improving our understanding of the seizure networks in drug-resistant epilepsy. The current available minimally invasive techniques are reasonable surgical alternatives to ablate or disrupt epileptogenic regions, although their sustained efficacy is still an active area of research. SUMMARY Epilepsy surgery is still underutilized worldwide. Every patient who continues with seizures despite adequate trials of two well selected and tolerated antiseizure medications should be evaluated for surgical candidacy. Collaboration between academic epilepsy centres is of paramount importance to answer long-standing questions in epilepsy surgery regarding the understanding of spatio-temporal dynamics in epileptogenic networks and its impact on surgical outcomes.
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16
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Alzoubi H, Nobile G, d'Amati A, Nobili L, Giacomini T, Tortora D, Gaggero G, Gianno F, Giangaspero F, Antonelli M, Consales A. Hyaline Protoplasmic Astrocytopathy in the Setting of Epilepsy. Am J Clin Pathol 2023; 159:120-128. [PMID: 36495294 DOI: 10.1093/ajcp/aqac145] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 10/24/2022] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES Cerebral hyaline protoplasmic astrocytopathy (HPA) is a clinicopathologic entity characterized by eosinophilic cytoplasmic inclusions within astrocytes. It has been observed in a subset of patients with early-onset epilepsy, brain malformations, and developmental delay. The exact association of this entity with epilepsy is still unknown. This report, with its review of the literature, aims to summarize HPA features to raise awareness regarding this entity. METHODS We report on 2 HPA cases and critically review the literature. RESULTS Approximately 42 cases of HPA have been reported, including the 2 cases presented here, consisting of 23 female and 19 male patients. Patient age ranged from 3 to 39 years. All patients had early-onset seizures (3-20 months of age), ranging from partial to generalized, that were refractory despite treatment with antiepileptic drugs. Postoperative follow-up intervals ranged from 2 to 93 months, and the clinical outcome was graded according to the Engel classification, showing variable results. CONCLUSIONS Clinicians should consider HPA in differential diagnosis in patients with intractable seizures, especially when they are associated with developmental delay and brain malformations. Increasing awareness of this entity among pathologists may promote better understanding of this condition as well as better diagnosis and treatment for these patients.
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Affiliation(s)
- Hiba Alzoubi
- Department of Basic Medical Sciences, Faculty of Medicine, Yarmouk University, Irbid, Jordan
| | - Giulia Nobile
- Unit of Child Neuropsychiatry, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Antonio d'Amati
- Anatomic Pathology Unit, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy.,Department of Radiology, Oncology and Anatomic Pathology, University La Sapienza, Rome, Italy
| | - Lino Nobili
- Unit of Child Neuropsychiatry, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Thea Giacomini
- Unit of Child Neuropsychiatry, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Domenico Tortora
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Gabriele Gaggero
- Ospedale Policlinico, San Martino IRCCS, Anatomic Pathology Unit, Genoa, Italy
| | - Francesca Gianno
- Department of Radiology, Oncology and Anatomic Pathology, University La Sapienza, Rome, Italy
| | - Felice Giangaspero
- Department of Radiology, Oncology and Anatomic Pathology, University La Sapienza, Rome, Italy
| | - Manila Antonelli
- Department of Radiology, Oncology and Anatomic Pathology, University La Sapienza, Rome, Italy
| | - Alessandro Consales
- Division of Neurosurgery, IRCCS Giannini Gaslini Children's Hospital, Genoa, Italy
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17
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Mao L, Zheng G, Cai Y, Luo W, Zhang Q, Peng W, Ding J, Wang X. Frontotemporal phase lag index correlates with seizure severity in patients with temporal lobe epilepsy. Front Neurol 2022; 13:855842. [DOI: 10.3389/fneur.2022.855842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 10/18/2022] [Indexed: 12/05/2022] Open
Abstract
ObjectivesTo find the brain network indicators correlated with the seizure severity in temporal lobe epilepsy (TLE) by graph theory analysis.MethodsWe enrolled 151 patients with TLE and 36 age- and sex-matched controls with video-EEG monitoring. The 90-s interictal EEG data were acquired. We adopted a network analyzing pipeline based on graph theory to quantify and localize their functional networks, including weighted classical network, minimum spanning tree, community structure, and LORETA. The seizure severities were evaluated using the seizure frequency, drug-resistant epilepsy (DRE), and VA-2 scores.ResultsOur network analysis pipeline showed ipsilateral frontotemporal activation in patients with TLE. The frontotemporal phase lag index (PLI) values increased in the theta band (4–7 Hz), which were elevated in patients with higher seizure severities (P < 0.05). Multivariate linear regression analysis showed that the VA-2 scores were independently correlated with frontotemporal PLI values in the theta band (β = 0.259, P = 0.001) and age of onset (β = −0.215, P = 0.007).SignificanceThis study illustrated that the frontotemporal PLI in the theta band independently correlated with seizure severity in patients with TLE. Our network analysis provided an accessible approach to guide the treatment strategy in routine clinical practice.
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18
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McGrath H, Zaveri HP, Collins E, Jafar T, Chishti O, Obaid S, Ksendzovsky A, Wu K, Papademetris X, Spencer DD. High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter. Sci Rep 2022; 12:18778. [PMID: 36335146 PMCID: PMC9637135 DOI: 10.1038/s41598-022-21543-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022] Open
Abstract
Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial electroencephalography, a technique which has historically provided pioneering advances in our understanding of brain structure-function relationships. We used a consensus boundary mapping approach combining anatomical designations in Duvernoy's Atlas of the Human Brain, a widely recognized textbook of human brain anatomy, with the anatomy of the MNI152 template and the magnetic resonance imaging scans of an epilepsy surgery cohort. The Yale Brain Atlas consists of 690 one-square centimeter parcels based around conserved anatomical features and each with a unique identifier to communicate anatomically unambiguous localization. We report on the methodology we used to create the Atlas along with the findings of a neuroimaging study assessing the accuracy and clinical usefulness of cortical localization using the Atlas. We also share our vision for the Atlas as a tool in the clinical and research neurosciences, where it may facilitate precise localization of data on the cortex, accurate description of anatomical locations, and modern data science approaches using standardized brain regions.
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Affiliation(s)
- Hari McGrath
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA.
- GKT School of Medical Education, King's College London, London, UK.
| | - Hitten P Zaveri
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Evan Collins
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Yale School of Engineering and Applied Science, New Haven, CT, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Tamara Jafar
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Omar Chishti
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Yale School of Engineering and Applied Science, New Haven, CT, USA
| | - Sami Obaid
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Alexander Ksendzovsky
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kun Wu
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Engineering, Yale School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Yale School of Medicine, New Haven, CT, USA
| | - Dennis D Spencer
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
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19
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Miron G, Müller PM, Holtkamp M. Diagnostic and prognostic value of EEG patterns recorded on foramen ovale and epidural peg electrodes. Clin Neurophysiol 2022; 143:107-115. [DOI: 10.1016/j.clinph.2022.08.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 07/28/2022] [Accepted: 08/17/2022] [Indexed: 11/03/2022]
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20
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Boddeti U, McAfee D, Khan A, Bachani M, Ksendzovsky A. Responsive Neurostimulation for Seizure Control: Current Status and Future Directions. Biomedicines 2022; 10:2677. [PMID: 36359197 PMCID: PMC9687706 DOI: 10.3390/biomedicines10112677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/13/2022] [Accepted: 10/15/2022] [Indexed: 10/29/2023] Open
Abstract
Electrocorticography (ECoG) data are commonly obtained during drug-resistant epilepsy (DRE) workup, in which subdural grids and stereotaxic depth electrodes are placed on the cortex for weeks at a time, with the goal of elucidating seizure origination. ECoG data can also be recorded from neuromodulatory devices, such as responsive neurostimulation (RNS), which involves the placement of electrodes deep in the brain. Of the neuromodulatory devices, RNS is the first to use recorded ECoG data to direct the delivery of electrical stimulation in order to control seizures. In this review, we first introduced the clinical management for epilepsy, and discussed the steps from seizure onset to surgical intervention. We then reviewed studies discussing the emergence and therapeutic mechanism behind RNS, and discussed why RNS may be underperforming despite an improved seizure detection mechanism. We discussed the potential utility of incorporating machine learning techniques to improve seizure detection in RNS, and the necessity to change RNS targets for stimulation, in order to account for the network theory of epilepsy. We concluded by commenting on the current and future status of neuromodulation in managing epilepsy, and the role of predictive algorithms to improve outcomes.
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Affiliation(s)
- Ujwal Boddeti
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Darrian McAfee
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Anas Khan
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Muzna Bachani
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Alexander Ksendzovsky
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
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21
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Moosavi SA, Jirsa VK, Truccolo W. Critical dynamics in the spread of focal epileptic seizures: Network connectivity, neural excitability and phase transitions. PLoS One 2022; 17:e0272902. [PMID: 35998146 PMCID: PMC9397939 DOI: 10.1371/journal.pone.0272902] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 07/29/2022] [Indexed: 11/24/2022] Open
Abstract
Focal epileptic seizures can remain localized or, alternatively, spread across brain areas, often resulting in impairment of cognitive function and loss of consciousness. Understanding the factors that promote spread is important for developing better therapeutic approaches. Here, we show that: (1) seizure spread undergoes “critical” phase transitions in models (epileptor-networks) that capture the neural dynamics of spontaneous seizures while incorporating patient-specific brain network connectivity, axonal delays and identified epileptogenic zones (EZs). We define a collective variable for the spreading dynamics as the spread size, i.e. the number of areas or nodes in the network to which a seizure has spread. Global connectivity strength and excitability in the surrounding non-epileptic areas work as phase-transition control parameters for this collective variable. (2) Phase diagrams are predicted by stability analysis of the network dynamics. (3) In addition, the components of the Jacobian’s leading eigenvector, which tend to reflect the connectivity strength and path lengths from the EZ to surrounding areas, predict the temporal order of network-node recruitment into seizure. (4) However, stochastic fluctuations in spread size in a near-criticality region make predictability more challenging. Overall, our findings support the view that within-patient seizure-spread variability can be characterized by phase-transition dynamics under transient variations in network connectivity strength and excitability across brain areas. Furthermore, they point to the potential use and limitations of model-based prediction of seizure spread in closed-loop interventions for seizure control.
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Affiliation(s)
- S. Amin Moosavi
- Department of Neuroscience, Brown University, Providence, RI, United States of America
| | - Viktor K. Jirsa
- Aix Marseille University, INSERM, INS, Institut de Neurosciences de Système, Marseille, France
| | - Wilson Truccolo
- Department of Neuroscience, Brown University, Providence, RI, United States of America
- Carney Institute for Brain Science, Brown University, Providence, RI, United States of America
- * E-mail:
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22
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Sivaraju A, Hirsch L, Gaspard N, Farooque P, Gerrard J, Xu Y, Deng Y, Damisah E, Blumenfeld H, Spencer DD. Factors Predicting Outcome After Intracranial EEG Evaluation in Patients With Medically Refractory Epilepsy. Neurology 2022; 99:e1-e10. [PMID: 35508395 PMCID: PMC9259091 DOI: 10.1212/wnl.0000000000200569] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 03/04/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The aim of this study was to identify predictors of a resective surgery and subsequent seizure freedom following intracranial EEG (ICEEG) for seizure-onset localization. METHODS This is a retrospective chart review of 178 consecutive patients with medically refractory epilepsy who underwent ICEEG monitoring from 2002 to 2015. Univariable and multivariable regression analysis identified independent predictors of resection vs other options. Stepwise Akaike information criteria with the aid of clinical consideration were used to select the best multivariable model for predicting resection and outcome. Discrete time survival analysis was used to analyze the factors predicting seizure-free outcome. Cumulative probability of seizure freedom was analyzed using Kaplan-Meier curves and compared between resection and nonresection groups. Additional univariate analysis was performed on 8 select clinical scenarios commonly encountered during epilepsy surgical evaluations. RESULTS Multivariable analysis identified the presence of a lesional MRI, presurgical hypothesis suggesting temporal lobe onset, and a nondominant hemisphere implant as independent predictors of resection (p < 0.0001, area under the receiver operating characteristic curve 0.80, 95% CI 0.73-0.87). Focal ICEEG onset and undergoing a resective surgery predicted absolute seizure freedom at the 5-year follow-up. Patients who underwent resective surgery were more likely to be seizure-free at 5 years compared with continued medical treatment or neuromodulation (60% vs 7%; p < 0.0001, hazard ratio 0.16, 95% CI 0.09-0.28). Even patients thought to have unfavorable predictors (nonlesional MRI or extratemporal lobe hypothesis or dominant hemisphere implant) had ≥50% chance of seizure freedom at 5 years if they underwent resection. DISCUSSION Unfavorable predictors, including having nonlesional extratemporal epilepsy, should not deter a thorough presurgical evaluation, including with invasive recordings in many cases. Resective surgery without functional impairment offers the best chance for sustained seizure freedom and should always be considered first. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that the presence of a lesional MRI, presurgical hypothesis suggesting temporal lobe onset, and a nondominant hemisphere implant are independent predictors of resection. Focal ICEEG onset and undergoing resection are independent predictors of 5-year seizure freedom.
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Affiliation(s)
- Adithya Sivaraju
- From the Comprehensive Epilepsy Center (A.S., L.H., N.G., P.F., H.B.), Department of Neurology, Yale University School of Medicine, New Haven, CT; Service de Neurologie (N.G.), Université Libre de Bruxelles-Hôpital Erasme, Belgium; Comprehensive Epilepsy Center (J.G., E.D., D.D.S.), Department of Neurosurgery, Yale University School of Medicine, New Haven; and Yale Center for Analytical Sciences (Y.X., Y.D.), Yale School of Public Health, New Haven, CT.
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23
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Paredes-Aragon E, AlKhaldi NA, Ballesteros-Herrera D, Mirsattari SM. Stereo-Encephalographic Presurgical Evaluation of Temporal Lobe Epilepsy: An Evolving Science. Front Neurol 2022; 13:867458. [PMID: 35720095 PMCID: PMC9197919 DOI: 10.3389/fneur.2022.867458] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 04/25/2022] [Indexed: 11/15/2022] Open
Abstract
Drug-resistant epilepsy is present in nearly 30% of patients. Resection of the epileptogenic zone has been found to be the most effective in achieving seizure freedom. The study of temporal lobe epilepsy for surgical treatment is extensive and complex. It involves a multidisciplinary team in decision-making with initial non-invasive studies (Phase I), providing 70% of the required information to elaborate a hypothesis and treatment plans. Select cases present more complexity involving bilateral clinical or electrographic manifestations, have contradicting information, or may involve deeper structures as a part of the epileptogenic zone. These cases are discussed by a multidisciplinary team of experts with a hypothesis for invasive methods of study. Subdural electrodes were once the mainstay of invasive presurgical evaluation and in later years most Comprehensive Epilepsy Centers have shifted to intracranial recordings. The intracranial recording follows original concepts since its development by Bancaud and Talairach, but great advances have been made in the field. Stereo-electroencephalography is a growing field of study, treatment, and establishment of seizure pattern complexities. In this comprehensive review, we explore the indications, usefulness, discoveries in interictal and ictal findings, pitfalls, and advances in the science of presurgical stereo-encephalography for temporal lobe epilepsy.
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Affiliation(s)
- Elma Paredes-Aragon
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Norah A AlKhaldi
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Neurology Department, King Fahad Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Daniel Ballesteros-Herrera
- Neurosurgery Department, National Institute of Neurology and Neurosurgery "Dr. Manuel Velasco Suárez", Mexico City, Mexico
| | - Seyed M Mirsattari
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Departments of Clinical Neurological Sciences, Diagnostic Imaging, Biomedical Imaging and Psychology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
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24
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Gummadavelli A, Englot DJ, Schwalb JM, Wu C, Gonzalez-Martinez J, Niemat J, Gerrard JL. ASSFN Position Statement on Deep Brain Stimulation for Medication-Refractory Epilepsy. Neurosurgery 2022; 90:636-641. [PMID: 35271523 PMCID: PMC9514731 DOI: 10.1227/neu.0000000000001923] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 01/12/2022] [Indexed: 11/19/2022] Open
Abstract
Neuromodulation has taken a foothold in the landscape of surgical treatment for medically refractory epilepsies and offers additional surgical treatment options for patients who are not candidates for resective/ablative surgery. Approximately one third of patients with epilepsy suffer with medication-refractory epilepsy. A persistent underuse of epilepsy surgery exists. Neuromodulation treatments including deep brain stimulation (DBS) expand the surgical options for patients with epilepsy and provide options for patients who are not candidates for resective surgery. DBS of the bilateral anterior nucleus of the thalamus is an Food and Drug Administration-approved, safe, and efficacious treatment option for patients with refractory focal epilepsy. The purpose of this consensus position statement is to summarize evidence, provide recommendations, and identify indications and populations for future investigation in DBS for epilepsy. The recommendations of the American Society of Functional and Stereotactic Neurosurgeons are based on several randomized and blinded clinical trials with high-quality data to support the use of DBS to the anterior nucleus of the thalamus for the treatment of refractory focal-onset seizures.
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Affiliation(s)
- Abhijeet Gummadavelli
- Department of Neurosurgery, Yale University School of Medicine, New Haven, Connecticut, USA;
| | - Dario J. Englot
- Department of Neurological Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee, USA;
| | - Jason M. Schwalb
- Department of Neurological Surgery, Henry Ford Health System, Detroit, Michigan, USA;
| | - Chengyuan Wu
- Department of Neurological Surgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA;
| | - Jorge Gonzalez-Martinez
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA;
| | - Joseph Niemat
- Department of Neurological Surgery, University of Louisville School of Medicine, Louisville, Kentucky, USA
| | - Jason L. Gerrard
- Department of Neurosurgery, Yale University School of Medicine, New Haven, Connecticut, USA;
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25
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O'Hara NB, Lee MH, Juhász C, Asano E, Jeong JW. Diffusion tractography predicts propagated high-frequency activity during epileptic spasms. Epilepsia 2022; 63:1787-1798. [PMID: 35388455 DOI: 10.1111/epi.17251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 03/28/2022] [Accepted: 04/05/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVE Determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare observed propagation patterns across patients with successful or unsuccessful surgical outcomes. METHODS Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion MRI tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated. Properties of this structural network were used to predict oscillation onset times and amplitudes, and this relationship was compared across patients who did and did not achieve seizure freedom following resective surgery. RESULTS Onset propagation patterns were relatively consistent across each patients' spasm events. An electrode's average ictal oscillation onset latency was most significantly associated with the length of direct corticocortical tracts connecting to the area with the earliest average oscillation onset (p < .001, model R2 = 0.54). Moreover, patients demonstrating a faster propagation of ictal oscillation signals within the corticocortical network were more likely to have seizure recurrence following resective surgery (p = .039). Ictal oscillation amplitude was also associated with connecting tractography length and weighted fractional anisotropy (FA) measures along these pathways (p = .002/.030, model R2 = 0.31/0.25). Characteristics of analogous corticothalamic pathways did not show significant associations with ictal oscillation onset latency or amplitude. SIGNIFICANCE Spatiotemporal propagation patterns of high-frequency activity in epileptic spasms align with length and FA measures from onset-originating corticocortical pathways. Considering data in this individualized framework may help inform surgical decision making and expectations of surgical outcomes.
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Affiliation(s)
- Nolan B O'Hara
- Wayne State University (WSU) Translational Neuroscience Program.,Children's Hospital of Michigan Translational Imaging Laboratory
| | - Min-Hee Lee
- Children's Hospital of Michigan Translational Imaging Laboratory
| | - Csaba Juhász
- Wayne State University (WSU) Translational Neuroscience Program.,Children's Hospital of Michigan Translational Imaging Laboratory.,WSU Department of Pediatrics.,WSU Department of Neurology
| | - Eishi Asano
- Wayne State University (WSU) Translational Neuroscience Program.,Children's Hospital of Michigan Translational Imaging Laboratory.,WSU Department of Pediatrics.,WSU Department of Neurology
| | - Jeong-Won Jeong
- Wayne State University (WSU) Translational Neuroscience Program.,Children's Hospital of Michigan Translational Imaging Laboratory.,WSU Department of Pediatrics.,WSU Department of Neurology
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26
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Adotevi N, Kapur J. Focal impaired awareness seizures in a rodent model: A functional anatomy. Epilepsia Open 2022; 7:110-123. [PMID: 34822222 PMCID: PMC8886100 DOI: 10.1002/epi4.12563] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 11/17/2021] [Accepted: 11/23/2021] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE Patients with temporal lobe epilepsy (TLE) frequently report debilitating comorbidities such as memory impairments, anxiety, and depression. An extensive neuronal network generates epileptic seizures and associated comorbidities, but a detailed description of this network is unavailable, which requires the generation of neuronal activation maps in experimental animals. METHODS We recorded electrographic seizures from the hippocampi during a kindling-evoked focal impaired awareness seizure with observed freezing, facial twitching, and involuntary head bobbing. We mapped seizure circuits activated during these seizures by permanently tagging neurons through activity-induced immediate early genes, combined with immunohistochemical approaches. RESULTS There was bilateral activation of circuits necessary for memory consolidation, including the hippocampal complex, entorhinal cortex, cingulate gyrus, retrosplenial cortex, piriform cortex, and septohippocampal complex in kindled animals compared with unstimulated awake behaving mice. Neuronal circuits in the ventral hippocampus, amygdala, and anterior cingulate cortex, which regulate the stress response of hypothalamic-pituitary-adrenal axis, were also markedly activated during a focal impaired awareness seizure. SIGNIFICANCE This study highlights neuronal circuits preferentially activated during a focal awareness impaired seizure in a rodent model. Many of the seizure-activated neuronal circuits are critical modulators of memory consolidation and long-term stress/depression response. The hijack of these memory and depression regulatory systems by a focal seizure could account for the frequent reports of comorbidities such as memory impairment and depression in many TLE patients.
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Affiliation(s)
- Nadia Adotevi
- Department of NeurologyUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Jaideep Kapur
- Department of NeurologyUniversity of VirginiaCharlottesvilleVirginiaUSA
- UVA Brain InstituteUniversity of VirginiaCharlottesvilleVirginiaUSA
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27
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Scheid BH, Bernabei JM, Khambhati AN, Mouchtaris S, Jeschke J, Bassett DS, Becker D, Davis KA, Lucas T, Doyle W, Chang EF, Friedman D, Rao VR, Litt B. Intracranial electroencephalographic biomarker predicts effective responsive neurostimulation for epilepsy prior to treatment. Epilepsia 2022; 63:652-662. [PMID: 34997577 PMCID: PMC9887634 DOI: 10.1111/epi.17163] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/22/2021] [Accepted: 12/27/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Despite the overall success of responsive neurostimulation (RNS) therapy for drug-resistant focal epilepsy, clinical outcomes in individuals vary significantly and are hard to predict. Biomarkers that indicate the clinical efficacy of RNS-ideally before device implantation-are critically needed, but challenges include the intrinsic heterogeneity of the RNS patient population and variability in clinical management across epilepsy centers. The aim of this study is to use a multicenter dataset to evaluate a candidate biomarker from intracranial electroencephalographic (iEEG) recordings that predicts clinical outcome with subsequent RNS therapy. METHODS We assembled a federated dataset of iEEG recordings, collected prior to RNS implantation, from a retrospective cohort of 30 patients across three major epilepsy centers. Using ictal iEEG recordings, each center independently calculated network synchronizability, a candidate biomarker indicating the susceptibility of epileptic brain networks to RNS therapy. RESULTS Ictal measures of synchronizability in the high-γ band (95-105 Hz) significantly distinguish between good and poor RNS responders after at least 3 years of therapy under the current RNS therapy guidelines (area under the curve = .83). Additionally, ictal high-γ synchronizability is inversely associated with the degree of therapeutic response. SIGNIFICANCE This study provides a proof-of-concept roadmap for collaborative biomarker evaluation in federated data, where practical considerations impede full data sharing across centers. Our results suggest that network synchronizability can help predict therapeutic response to RNS therapy. With further validation, this biomarker could facilitate patient selection and help avert a costly, invasive intervention in patients who are unlikely to benefit.
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Affiliation(s)
- Brittany H. Scheid
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John M. Bernabei
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ankit N. Khambhati
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA,Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Sofia Mouchtaris
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jay Jeschke
- Comprehensive Epilepsy Center, NYU Langone Health, New York, New York, USA
| | - Dani S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Santa Fe Institute, Santa Fe, New Mexico, USA
| | - Danielle Becker
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kathryn A. Davis
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Timothy Lucas
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Werner Doyle
- Department of Neurosurgery, NYU Langone, New York, New York, USA
| | - Edward F. Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA,Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Daniel Friedman
- Comprehensive Epilepsy Center, NYU Langone Health, New York, New York, USA,Department of Neurology, NYU Langone, New York, New York, USA
| | - Vikram R. Rao
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Brian Litt
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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28
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Martins-Ferreira R, Leal B, Chaves J, Li T, Ciudad L, Rangel R, Santos A, Martins da Silva A, Pinho Costa P, Ballestar E. Epilepsy progression is associated with cumulative DNA methylation changes in inflammatory genes. Prog Neurobiol 2022; 209:102207. [DOI: 10.1016/j.pneurobio.2021.102207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 11/02/2021] [Accepted: 12/14/2021] [Indexed: 01/09/2023]
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29
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Zhang L, Zhou H, Zhang W, Ling X, Zeng C, Tang Y, Gan J, Tan Q, Hu X, Li H, Cheng B, Xu H, Guo Q. Electroclinical and Multimodality Neuroimaging Characteristics and Predictors of Post-Surgical Outcome in Focal Cortical Dysplasia Type IIIa. Front Bioeng Biotechnol 2022; 9:810897. [PMID: 35083208 PMCID: PMC8784525 DOI: 10.3389/fbioe.2021.810897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 11/26/2021] [Indexed: 11/18/2022] Open
Abstract
Focal cortical dysplasia (FCD) type IIIa is an easily ignored cause of intractable temporal lobe epilepsy. This study aimed to analyze the clinical, electrophysiological, and imaging characteristics in FCD type IIIa and to search for predictors associated with postoperative outcome in order to identify potential candidates for epilepsy surgery. We performed a retrospective review including sixty-six patients with FCD type IIIa who underwent resection for drug-resistant epilepsy. We evaluated the clinical, electrophysiological, and neuroimaging features for potential association with seizure outcome. Univariate and multivariate analyses were conducted to explore their predictive role on the seizure outcome. We demonstrated that thirty-nine (59.1%) patients had seizure freedom outcomes (Engel class Ia) with a median postsurgical follow-up lasting 29.5 months. By univariate analysis, duration of epilepsy (less than 12 years) (p = 0.044), absence of contralateral insular lobe hypometabolism on PET/MRI (pLog-rank = 0.025), and complete resection of epileptogenic area (pLog-rank = 0.004) were associated with seizure outcome. The incomplete resection of the epileptogenic area (hazard ratio = 2.977, 95% CI 1.218–7.277, p = 0.017) was the only independent predictor for seizure recurrence after surgery by multivariate analysis. The results of past history, semiology, electrophysiological, and MRI were not associated with seizure outcomes. Carefully included patients with FCD type IIIa through a comprehensive evaluation of their clinical, electrophysiological, and neuroimaging characteristics can be good candidates for resection. Several preoperative factors appear to be predictive of the postoperative outcome and may help in optimizing the selection of ideal candidates to benefit from epilepsy surgery.
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Affiliation(s)
- Lingling Zhang
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China.,Department of Neurology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Hailing Zhou
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Wei Zhang
- Epilepsy Center, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Xueying Ling
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Chunyuan Zeng
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yongjin Tang
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jiefeng Gan
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Qinghua Tan
- Epilepsy Center, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Xiangshu Hu
- Epilepsy Center, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Hainan Li
- Department of Pathology, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Baijie Cheng
- Department of Pathology, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Hao Xu
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Qiang Guo
- Epilepsy Center, Guangdong 999 Brain Hospital, Guangzhou, China
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30
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Tang Y, Li W, Tao L, Li J, Long T, Li Y, Chen D, Hu S. Machine Learning-Derived Multimodal Neuroimaging of Presurgical Target Area to Predict Individual's Seizure Outcomes After Epilepsy Surgery. Front Cell Dev Biol 2022; 9:669795. [PMID: 35127691 PMCID: PMC8814443 DOI: 10.3389/fcell.2021.669795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 12/21/2021] [Indexed: 11/16/2022] Open
Abstract
Objectives: Half of the patients who have tailored resection of the suspected epileptogenic zone for drug-resistant epilepsy have recurrent postoperative seizures. Although neuroimaging has become an indispensable part of delineating the epileptogenic zone, no validated method uses neuroimaging of presurgical target area to predict an individual's post-surgery seizure outcome. We aimed to develop and validate a machine learning-powered approach incorporating multimodal neuroimaging of a presurgical target area to predict an individual's post-surgery seizure outcome in patients with drug-resistant focal epilepsy. Materials and Methods: One hundred and forty-one patients with drug-resistant focal epilepsy were classified either as having seizure-free (Engel class I) or seizure-recurrence (Engel class II through IV) at least 1 year after surgery. The presurgical magnetic resonance imaging, positron emission tomography, computed tomography, and postsurgical magnetic resonance imaging were co-registered for surgical target volume of interest (VOI) segmentation; all VOIs were decomposed into nine fixed views, then were inputted into the deep residual network (DRN) that was pretrained on Tiny-ImageNet dataset to extract and transfer deep features. A multi-kernel support vector machine (MKSVM) was used to integrate multiple views of feature sets and to predict seizure outcomes of the targeted VOIs. Leave-one-out validation was applied to develop a model for verifying the prediction. In the end, performance using this approach was assessed by calculating accuracy, sensitivity, and specificity. Receiver operating characteristic curves were generated, and the optimal area under the receiver operating characteristic curve (AUC) was calculated as a metric for classifying outcomes. Results: Application of DRN-MKSVM model based on presurgical target area neuroimaging demonstrated good performance in predicting seizure outcomes. The AUC ranged from 0.799 to 0.952. Importantly, the classification performance DRN-MKSVM model using data from multiple neuroimaging showed an accuracy of 91.5%, a sensitivity of 96.2%, a specificity of 85.5%, and AUCs of 0.95, which were significantly better than any other single-modal neuroimaging (all p ˂ 0.05). Conclusion: DRN-MKSVM, using multimodal compared with unimodal neuroimaging from the surgical target area, accurately predicted postsurgical outcomes. The preoperative individualized prediction of seizure outcomes in patients who have been judged eligible for epilepsy surgery could be conveniently facilitated. This may aid epileptologists in presurgical evaluation by providing a tool to explore various surgical options, offering complementary information to existing clinical techniques.
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Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Weikai Li
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
| | - Lue Tao
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Tingting Long
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Yulai Li
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Dengming Chen
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Changsha, China
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31
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Individual [ 18F]FDG PET and functional MRI based on simultaneous PET/MRI may predict seizure recurrence after temporal lobe epilepsy surgery. Eur Radiol 2022; 32:3880-3888. [PMID: 35024947 DOI: 10.1007/s00330-021-08490-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 10/21/2021] [Accepted: 11/28/2021] [Indexed: 01/11/2023]
Abstract
OBJECTIVES To investigate the individual measures of brain glucose metabolism, neural activity obtained from simultaneous 18[F]FDG PET/MRI, and their association with surgical outcomes in medial temporal lobe epilepsy due to hippocampal sclerosis (mTLE-HS). METHODS Thirty-nine unilateral mTLE-HS patients who underwent anterior temporal lobectomy were classified as having completely seizure-free (Engel class IA; n = 22) or non-seizure-free (Engel class IB-IV; n = 17) outcomes at 1 year after surgery. Preoperative [18F]FDG PET and functional MRI (fMRI) were obtained from a simultaneous PET/MRI scanner, and individual glucose metabolism and fractional amplitude of low-frequency fluctuation (fALFF) were evaluated by standardizing these with respect to healthy controls. These abnormality measures and clinical data from each patient were incorporated into a machine learning framework (gradient boosting decision tree and logistic regression analysis) to estimate seizure recurrence. The predictive values of features were evaluated by the receiver operating characteristic (ROC) curve in the training and test cohorts. RESULTS The machine learning classification model showed [18F]FDG PET and fMRI variations in contralateral hippocampal network and age of onset identify unfavorable surgical outcomes effectively. In the validation dataset, the logistic regression model with [18F]FDG PET and fALFF obtained from simultaneous [18F]FDG PET/MRI gained the maximum area under the ROC curve of 0.905 for seizure recurrence, higher than 0.762 with 18[F]-FDG PET, and 0.810 with fALFF alone. CONCLUSION Machine learning model suggests individual [18F]FDG PET and fMRI variations in contralateral hippocampal network based on 18[F]-FDG PET/MRI could serve as a potential biomarker of unfavorable surgical outcomes. KEY POINTS • Individual [18F]FDG PET and fMRI obtained from preoperative [18F]FDG PET/MR were investigated. • Individual differences were further assessed based on a seizure propagation network. • Machine learning can classify surgical outcomes with 90.5% accuracy.
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32
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Eid T. Transforming Glia to Neurons Effectively Treats Temporal Lobe Seizures. Epilepsy Curr 2022; 22:130-131. [PMID: 35444496 PMCID: PMC8988719 DOI: 10.1177/15357597211073013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Affiliation(s)
- Tore Eid
- Departments of Laboratory Medicine of Neurosurgery and of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT, USA
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33
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Electrically stimulated auras as a potential biomarker of the epileptogenic zone. Epilepsy Behav 2021; 122:108116. [PMID: 34139619 DOI: 10.1016/j.yebeh.2021.108116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 05/24/2021] [Accepted: 05/25/2021] [Indexed: 11/23/2022]
Abstract
Electrocortical stimulation mapping (ESM) is often performed in patients undergoing stereoelectroencephalography (SEEG) prior to epilepsy surgery, with the goal of identifying functional cortex and preserving it postoperatively. ESM may also evoke a patient's typical seizure semiology. The purpose of this study was to determine whether the sites at which typical auras are evoked during ESM are associated with other known clinical and electrophysiologic biomarkers of the epileptogenic zone: the seizure onset zone (SOZ), the early spread zone (ES), and high-frequency oscillations (HFOs). We found that the sites at which auras were provoked were not consistently associated with known biomarkers (p = 0.09). We conclude that evoked auras during ESM may reflect electrical spread rather than true epileptogenicity, and that a larger study is needed to assess their potential value as independent epileptic biomarkers.
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34
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Saute RL, Peixoto-Santos JE, Velasco TR, Leite JP. Improving surgical outcome with electric source imaging and high field magnetic resonance imaging. Seizure 2021; 90:145-154. [PMID: 33608134 DOI: 10.1016/j.seizure.2021.02.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/26/2021] [Accepted: 02/04/2021] [Indexed: 12/14/2022] Open
Abstract
While most patients with focal epilepsy present with clear structural abnormalities on standard, 1.5 or 3 T MRI, some patients are MRI-negative. For those, quantitative MRI techniques, such as volumetry, voxel-based morphometry, and relaxation time measurements can aid in finding the epileptogenic focus. High-field MRI, just recently approved for clinical use by the FDA, increases the resolution and, in several publications, was shown to improve the detection of focal cortical dysplasias and mild cortical malformations. For those cases without any tissue abnormality in neuroimaging, even at 7 T, scalp EEG alone is insufficient to delimitate the epileptogenic zone. They may benefit from the use of high-density EEG, in which the increased number of electrodes helps improve spatial sampling. The spatial resolution of even low-density EEG can benefit from electric source imaging techniques, which map the source of the recorded abnormal activity, such as interictal epileptiform discharges, focal slowing, and ictal rhythm. These EEG techniques help localize the irritative, functional deficit, and seizure-onset zone, to better estimate the epileptogenic zone. Combining those technologies allows several drug-resistant cases to be submitted to surgery, increasing the odds of seizure freedom and providing a must needed hope for patients with epilepsy.
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Affiliation(s)
- Ricardo Lutzky Saute
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of Sao Paulo, Brazil
| | - Jose Eduardo Peixoto-Santos
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Paulista School of Medicine, Unifesp, Brazil
| | - Tonicarlo R Velasco
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of Sao Paulo, Brazil
| | - Joao Pereira Leite
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of Sao Paulo, Brazil.
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35
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Duckrow RB, Ceolini E, Zaveri HP, Brooks C, Ghosh A. Artificial neural network trained on smartphone behavior can trace epileptiform activity in epilepsy. iScience 2021; 24:102538. [PMID: 34308281 PMCID: PMC8257969 DOI: 10.1016/j.isci.2021.102538] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 04/28/2021] [Accepted: 05/11/2021] [Indexed: 12/23/2022] Open
Abstract
A range of abnormal electrical activity patterns termed epileptiform discharges can occur in the brains of persons with epilepsy. These epileptiform discharges can be monitored and recorded with implanted devices that deliver therapeutic neurostimulation. These continuous recordings provide an opportunity to study the behavioral correlates of epileptiform discharges as the patients go about their daily lives. Here, we captured the smartphone touchscreen interactions in eight patients in conjunction with electrographic recordings (accumulating 35,714 h) and by using an artificial neural network model addressed if the behavior reflected the epileptiform discharges. The personalized model outputs based on smartphone behavioral inputs corresponded well with the observed electrographic data (R: 0.2-0.6, median 0.4). The realistic reconstructions of epileptiform activity based on smartphone use demonstrate how day-to-day digital behavior may be converted to personalized markers of disease activity in epilepsy.
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Affiliation(s)
| | - Enea Ceolini
- QuantActions GmbH, Lausanne, Switzerland
- Institute of Psychology, Leiden University, Wassenaarseweg 52, Leiden 2333 AK, The Netherlands
| | | | - Cornell Brooks
- Department of Neurology, Yale University, New Haven, CT, USA
- Amherst College, Amherst, MA, USA
| | - Arko Ghosh
- Institute of Psychology, Leiden University, Wassenaarseweg 52, Leiden 2333 AK, The Netherlands
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36
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Rapidly spreading seizures arise from large-scale functional brain networks in focal epilepsy. Neuroimage 2021; 237:118104. [PMID: 33933597 DOI: 10.1016/j.neuroimage.2021.118104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 04/22/2021] [Accepted: 04/25/2021] [Indexed: 11/21/2022] Open
Abstract
It remains unclear whether epileptogenic networks in focal epilepsy develop on physiological networks. This work aimed to explore the association between the rapid spread of ictal fast activity (IFA), a proposed biomarker for epileptogenic networks, and the functional connectivity or networks of healthy subjects. We reviewed 45 patients with focal epilepsy who underwent electrocorticographic (ECoG) recordings to identify the patients showing the rapid spread of IFA. IFA power was quantified as normalized beta-gamma band power. Using published resting-state functional magnetic resonance imaging databases, we estimated resting-state functional connectivity of healthy subjects (RSFC-HS) and resting-state networks of healthy subjects (RSNs-HS) at the locations corresponding to the patients' electrodes. We predicted the IFA power of each electrode based on RSFC-HS between electrode locations (RSFC-HS-based prediction) using a recently developed method, termed activity flow mapping. RSNs-HS were identified using seed-based and atlas-based methods. We compared IFA power with RSFC-HS-based prediction or RSNs-HS using non-parametric correlation coefficients. RSFC and seed-based RSNs of each patient (RSFC-PT and seed-based RSNs-PT) were also estimated using interictal ECoG data and compared with IFA power in the same way as RSFC-HS and seed-based RSNs-HS. Spatial autocorrelation-preserving randomization tests were performed for significance testing. Nine patients met the inclusion criteria. None of the patients had reflex seizures. Six patients showed pathological evidence of a structural etiology. In total, we analyzed 49 seizures (2-13 seizures per patient). We observed significant correlations between IFA power and RSFC-HS-based prediction, seed-based RSNs-HS, or atlas-based RSNs-HS in 28 (57.1%), 21 (42.9%), and 28 (57.1%) seizures, respectively. Thirty-two (65.3%) seizures showed a significant correlation with either seed-based or atlas-based RSNs-HS, but this ratio varied across patients: 27 (93.1%) of 29 seizures in six patients correlated with either of them. Among atlas-based RSNs-HS, correlated RSNs-HS with IFA power included the default mode, control, dorsal attention, somatomotor, and temporal-parietal networks. We could not obtain RSFC-PT and RSNs-PT in one patient due to frequent interictal epileptiform discharges. In the remaining eight patients, most of the seizures showed significant correlations between IFA power and RSFC-PT-based prediction or seed-based RSNs-PT. Our study provides evidence that the rapid spread of IFA in focal epilepsy can arise from physiological RSNs. This finding suggests an overlap between epileptogenic and functional networks, which may explain why functional networks in patients with focal epilepsy frequently disrupt.
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37
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Kleen JK, Speidel BA, Baud MO, Rao VR, Ammanuel SG, Hamilton LS, Chang EF, Knowlton RC. Accuracy of omni-planar and surface casting of epileptiform activity for intracranial seizure localization. Epilepsia 2021; 62:947-959. [PMID: 33634855 PMCID: PMC8276628 DOI: 10.1111/epi.16841] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 01/23/2021] [Accepted: 01/23/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Intracranial electroencephalography (ICEEG) recordings are performed for seizure localization in medically refractory epilepsy. Signal quantifications such as frequency power can be projected as heatmaps on personalized three-dimensional (3D) reconstructed cortical surfaces to distill these complex recordings into intuitive cinematic visualizations. However, simultaneously reconciling deep recording locations and reliably tracking evolving ictal patterns remain significant challenges. METHODS We fused oblique magnetic resonance imaging (MRI) slices along depth probe trajectories with cortical surface reconstructions and projected dynamic heatmaps using a simple mathematical metric of epileptiform activity (line-length). This omni-planar and surface casting of epileptiform activity approach (OPSCEA) thus illustrated seizure onset and spread among both deep and superficial locations simultaneously with minimal need for signal processing supervision. We utilized the approach on 41 patients at our center implanted with grid, strip, and/or depth electrodes for localizing medically refractory seizures. Peri-ictal data were converted into OPSCEA videos with multiple 3D brain views illustrating all electrode locations. Five people of varying expertise in epilepsy (medical student through epilepsy attending level) attempted to localize the seizure-onset zones. RESULTS We retrospectively compared this approach with the original ICEEG study reports for validation. Accuracy ranged from 73.2% to 97.6% for complete or overlapping onset lobe(s), respectively, and ~56.1% to 95.1% for the specific focus (or foci). Higher answer certainty for a given case predicted better accuracy, and scorers had similar accuracy across different training levels. SIGNIFICANCE In an era of increasing stereo-EEG use, cinematic visualizations fusing omni-planar and surface functional projections appear to provide a useful adjunct for interpreting complex intracranial recordings and subsequent surgery planning.
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Affiliation(s)
- Jonathan K Kleen
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Benjamin A Speidel
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Maxime O Baud
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Simon G Ammanuel
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Liberty S Hamilton
- Department of Speech, Language, and Hearing Sciences and Department of Neurology, The University of Texas at Austin, Austin, Texas, USA
| | - Edward F Chang
- Department of Neurological Surgery and Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Robert C Knowlton
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, California, USA
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38
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Dhaher R, Gruenbaum SE, Sandhu MRS, Ottestad-Hansen S, Tu N, Wang Y, Lee TSW, Deshpande K, Spencer DD, Danbolt NC, Zaveri HP, Eid T. Network-Related Changes in Neurotransmitters and Seizure Propagation During Rodent Epileptogenesis. Neurology 2021; 96:e2261-e2271. [PMID: 33722994 PMCID: PMC8166437 DOI: 10.1212/wnl.0000000000011846] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 01/29/2021] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE To test the hypothesis that glutamate and GABA are linked to the formation of epilepsy networks and the triggering of spontaneous seizures, we examined seizure initiation/propagation characteristics and neurotransmitter levels during epileptogenesis in a translationally relevant rodent model of mesial temporal lobe epilepsy. METHODS The glutamine synthetase (GS) inhibitor methionine sulfoximine was infused into one of the hippocampi in laboratory rats to create a seizure focus. Long-term video-intracranial EEG recordings and brain microdialysis combined with mass spectrometry were used to examine seizure initiation, seizure propagation, and extracellular brain levels of glutamate and GABA. RESULTS All seizures (n = 78 seizures, n = 3 rats) appeared first in the GS-inhibited hippocampus of all animals, followed by propagation to the contralateral hippocampus. Propagation time decreased significantly from 11.65 seconds early in epileptogenesis (weeks 1-2) to 6.82 seconds late in epileptogenesis (weeks 3-4, paired t test, p = 0.025). Baseline extracellular glutamate levels were 11.6-fold higher in the hippocampus of seizure propagation (7.3 µM) vs the hippocampus of seizure onset (0.63 µM, analysis of variance/Fisher least significant difference, p = 0.01), even though the concentrations of the major glutamate transporter proteins excitatory amino acid transporter subtypes 1 and 2 and xCT were unchanged between the brain regions. Finally, extracellular GABA in the seizure focus decreased significantly from baseline several hours before a spontaneous seizure (paired t test/false discovery rate). CONCLUSION The changes in glutamate and GABA suggest novel and potentially important roles of the amino acids in epilepsy network formation and in the initiation and propagation of spontaneous seizures.
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Affiliation(s)
- Roni Dhaher
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Shaun E Gruenbaum
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Mani Ratnesh S Sandhu
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Sigrid Ottestad-Hansen
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Nathan Tu
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Yue Wang
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Tih-Shih W Lee
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Ketaki Deshpande
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Dennis D Spencer
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Niels Christian Danbolt
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Hitten P Zaveri
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway
| | - Tore Eid
- From the Departments of Laboratory Medicine (R.D., M.R.S.S., N.T., Y.W., K.D., T.E.), Anesthesiology (S.E.G.), Neurosurgery (D.D.S.), Psychiatry (T.-S.W.L.), and Neurology (H.P.Z.), Yale School of Medicine, New Haven, CT; and Department of Molecular Medicine (S.O.-H., N.C.D.), Division of Anatomy, Institute for Basic Medical Sciences, University of Oslo, Norway.
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Gleichgerrcht E, Greenblatt AS, Kellermann TS, Rowland N, Vandergrift WA, Edwards J, Davis KA, Bonilha L. Patterns of seizure spread in temporal lobe epilepsy are associated with distinct white matter tracts. Epilepsy Res 2021; 171:106571. [PMID: 33582534 DOI: 10.1016/j.eplepsyres.2021.106571] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 01/31/2021] [Accepted: 02/03/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE It is commonly hypothesized that seizure spread patterns in patients with focal epilepsy are associated with structural brain pathways. However, this relationship is poorly understood and has not been fully demonstrated in patients with temporal lobe epilepsy. Here, we sought to determine whether directionality of seizure spread (DSS) is associated with specific cerebral white matter tracts in patients with temporal lobe epilepsy. METHODS Thirty-three adult patients with temporal lobe epilepsy who underwent stereoelectroencephalography (sEEG) and magnetic resonance diffusion tensor imaging (MR-DTI) as part of their standard-of-care clinical evaluation were included in the study. DSS was defined as anterior-posterior (AP) or medial-lateral (ML) spread based upon sEEG evaluation by two independent specialists who demonstrated excellent inter-rater agreement (Cohen's kappa = .92). DTI connectometry was used to assess differences between seizure spread pattern groups along major fiber pathways regarding fractional anisotropy (FA). RESULTS Twenty-four participants showed seizures with AP spread and nine participants showed seizures with ML spread. There were no significant differences between the groups on their demographic and clinical profile. Patients with ML seizures had higher FA along the corpus callosum and, to a lesser degree, some portions of the bilateral cingulate tracts. In contrast, patients with AP seizures had higher FA along several anterior-posterior white matter projections bundles, including the cingulate fasciculus and the inferior longitudinal, with significantly less involvement of the corpus callosum compared with ML seizures. SIGNIFICANCE This study confirms the hypothesis that the anatomical pattern of electrophysiological ictal propagation is associated with the structural reinforcement of supporting pathways in temporal lobe epilepsy. This observation can help elucidate mechanisms of ictal propagation and may guide future translational approaches to curtail seizure spread.
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Affiliation(s)
| | - Adam S Greenblatt
- Medical University of South Carolina, Charleston, SC, USA; University of Pennsylvania, Philadelphia, PA, USA
| | | | - Nathan Rowland
- Medical University of South Carolina, Charleston, SC, USA
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Abstract
PURPOSE OF REVIEW Epilepsy surgery is the therapy of choice for 30-40% of people with focal drug-resistant epilepsy. Currently only ∼60% of well selected patients become postsurgically seizure-free underlining the need for better tools to identify the epileptogenic zone. This article reviews the latest neurophysiological advances for EZ localization with emphasis on ictal EZ identification, interictal EZ markers, and noninvasive neurophysiological mapping procedures. RECENT FINDINGS We will review methods for computerized EZ assessment, summarize computational network approaches for outcome prediction and individualized surgical planning. We will discuss electrical stimulation as an option to reduce the time needed for presurgical work-up. We will summarize recent research regarding high-frequency oscillations, connectivity measures, and combinations of multiple markers using machine learning. This latter was shown to outperform single markers. The role of NREM sleep for best identification of the EZ interictally will be discussed. We will summarize recent large-scale studies using electrical or magnetic source imaging for clinical decision-making. SUMMARY New approaches based on technical advancements paired with artificial intelligence are on the horizon for better EZ identification. They are ultimately expected to result in a more efficient, less invasive, and less time-demanding presurgical investigation.
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Tang Y, Liao G, Li J, Long T, Li Y, Feng L, Chen D, Tang B, Hu S. FDG-PET Profiles of Extratemporal Metabolism as a Predictor of Surgical Failure in Temporal Lobe Epilepsy. Front Med (Lausanne) 2020; 7:605002. [PMID: 33425950 PMCID: PMC7793721 DOI: 10.3389/fmed.2020.605002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 11/23/2020] [Indexed: 11/30/2022] Open
Abstract
Objective: Metabolic abnormality in the extratemporal area on fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) is not an uncommon finding in drug-resistant temporal lobe epilepsy (TLE), however the correlation between extratemporal metabolic abnormalities and surgical long-term prognosis has not been fully elucidated. We aim to investigate FDG-PET extratemporal metabolic profiles predictive of failure in surgery for TLE patients. Methods: Eighty-two patients with unilateral TLE (48 female, 34 male; 25.6 ± 10.6 years old; 37 left TLE, 45 right TLE) and 30 healthy age-matched controls were enrolled. Patients were classified either as experiencing seizure-recurrence (SZR, Engel class II through IV) or seizure-free (SZF, Engel class I) at least 1 year after surgery. Regional cerebral metabolism was evaluated by FDG-PET with statistical parametric mapping (SPM12). Abnormal metabolic profiles and patterns on FDG-PET in SZR group were evaluated and compared with those of healthy control and SZF subjects on SPM12. Volume and intensity as well as special brain areas of abnormal metabolism in temporal and extratemporal regions were quantified and visualized. Results: With a median follow-up of 1.5 years, 60% of patients achieved Engel class I (SZF). SZR was associated with left TLE and widespread hypometabolism in FDG-PET visual assessment (both p < 0.05). All patients had hypometabolism in the ipsilateral temporal lobe but SZR was not correlated with volume or intensity of temporal hypometabolism (median, 1,456 vs. 1,040 mm3; p > 0.05). SZR was correlated with extratemporal metabolic abnormalities that differed according to lateralization: in right TLE, SZR exhibited larger volume in extratemporal areas compared to SZF (median, 11,060 vs. 2,112 mm3; p < 0.05). Surgical failure was characterized by Cingulum_Ant_R/L, Frontal_Inf_Orb_R abnormal metabolism in extratemporal regions. In left TLE, SZR presented a larger involvement of extratemporal areas similar to right TLE but with no significant (median, 5,873 vs. 3,464 mm3; p > 0.05), Cingulum_Ant_ R/L, Parietal_Inf_L, Postcentral_L, and Precuneus_R involved metabolic abnormalities were correlated with SZR. Conclusions: Extratemporal metabolic profiles detected by FDG-PET may indicate a prominent cause of TLE surgery failure and should be considered in predictive models for epilepsy surgery. Seizure control after surgery might be improved by investigating extratemporal areas as candidates for resection or neuromodulation.
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Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Guang Liao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Tingting Long
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Yulai Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Dengming Chen
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, China
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Landazuri P, Shih J, Leuthardt E, Ben-Haim S, Neimat J, Tovar-Spinoza Z, Chiang V, Spencer D, Sun D, Fecci P, Baumgartner J. A prospective multicenter study of laser ablation for drug resistant epilepsy – One year outcomes. Epilepsy Res 2020; 167:106473. [DOI: 10.1016/j.eplepsyres.2020.106473] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 08/21/2020] [Accepted: 09/17/2020] [Indexed: 10/23/2022]
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Percy J, Zaveri H, Duckrow RB, Gerrard J, Farooque P, Hirsch LJ, Spencer DD, Sivaraju A. Beyond implantation effect? Long-term seizure reduction and freedom following intracranial monitoring without additional surgical interventions. Epilepsy Behav 2020; 111:107231. [PMID: 32615416 DOI: 10.1016/j.yebeh.2020.107231] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 05/11/2020] [Accepted: 06/05/2020] [Indexed: 11/15/2022]
Abstract
The term 'implantation effect' is used to describe an immediate and transient improvement in seizure frequency following an intracranial study for seizure onset localization. We conducted a retrospective analysis of 190 consecutive patients undergoing intracranial electroencephalogram (EEG) monitoring, of whom 41 had no subsequent resection/ablation/stimulation; 33 had adequate data and follow-up time available for analysis. Analysis of seizure frequency following an intracranial study showed 36% (12/33) responder rate (>50% seizure reduction) at one year, decreasing and stabilizing at 20% from year 4 onwards. In addition, we describe three patients (9%) who had long term seizure freedom of more than five years following electrode implantation alone, two of whom had thalamic depth electrodes. Electrode implantation perhaps leads to a neuromodulatory effect sufficient enough to disrupt epileptogenic networks. Rarely, this may be significant enough to even result in long term seizure freedom, as seen in our three patients.
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Affiliation(s)
- Jennifer Percy
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States of America; Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Hitten Zaveri
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States of America
| | - Robert B Duckrow
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States of America
| | - Jason Gerrard
- Comprehensive Epilepsy Center, Department of Neurosurgery, Yale University, New Haven, CT, United States of America
| | - Pue Farooque
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States of America
| | - Lawrence J Hirsch
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States of America
| | - Dennis D Spencer
- Comprehensive Epilepsy Center, Department of Neurosurgery, Yale University, New Haven, CT, United States of America
| | - Adithya Sivaraju
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States of America.
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Narasimhan S, Kundassery KB, Gupta K, Johnson GW, Wills KE, Goodale SE, Haas K, Rolston JD, Naftel RP, Morgan VL, Dawant BM, González HFJ, Englot DJ. Seizure-onset regions demonstrate high inward directed connectivity during resting-state: An SEEG study in focal epilepsy. Epilepsia 2020; 61:2534-2544. [PMID: 32944945 DOI: 10.1111/epi.16686] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 08/15/2020] [Accepted: 08/17/2020] [Indexed: 01/06/2023]
Abstract
OBJECTIVE In patients with medically refractory focal epilepsy, stereotactic-electroencephalography (SEEG) can aid in localizing epileptogenic regions for surgical treatment. SEEG, however, requires long hospitalizations to record seizures, and ictal interpretation can be incomplete or inaccurate. Our recent work showed that non-directed resting-state analyses may identify brain regions as epileptogenic or uninvolved. Our present objective is to map epileptogenic networks in greater detail and more accurately identify seizure-onset regions using directed resting-state SEEG connectivity. METHODS In 25 patients with focal epilepsy who underwent SEEG, 2 minutes of resting-state, artifact-free, SEEG data were selected and functional connectivity was estimated. Using standard clinical interpretation, brain regions were classified into four categories: ictogenic, early propagation, irritative, or uninvolved. Three non-directed connectivity measures (mutual information [MI] strength, and imaginary coherence between and within regions) and four directed measures (partial directed coherence [PDC] and directed transfer function [DTF], inward and outward strength) were calculated. Logistic regression was used to generate a predictive model of ictogenicity. RESULTS Ictogenic regions had the highest and uninvolved regions had the lowest MI strength. Although both PDC and DTF inward strengths were highest in ictogenic regions, outward strengths did not differ among categories. A model incorporating directed and nondirected connectivity measures demonstrated an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.88 in predicting ictogenicity of individual regions. The AUC of this model was 0.93 when restricted to patients with favorable postsurgical seizure outcomes. SIGNIFICANCE Directed connectivity measures may help identify epileptogenic networks without requiring ictal recordings. Greater inward but not outward connectivity in ictogenic regions at rest may represent broad inhibitory input to prevent seizure generation.
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Affiliation(s)
- Saramati Narasimhan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Keshav B Kundassery
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kanupriya Gupta
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Graham W Johnson
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Kristin E Wills
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah E Goodale
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Kevin Haas
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John D Rolston
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Victoria L Morgan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Hernán F J González
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Dario J Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
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Finnema SJ, Toyonaga T, Detyniecki K, Chen MK, Dias M, Wang Q, Lin SF, Naganawa M, Gallezot JD, Lu Y, Nabulsi NB, Huang Y, Spencer DD, Carson RE. Reduced synaptic vesicle protein 2A binding in temporal lobe epilepsy: A [ 11 C]UCB-J positron emission tomography study. Epilepsia 2020; 61:2183-2193. [PMID: 32944949 DOI: 10.1111/epi.16653] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 07/23/2020] [Accepted: 07/24/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVE In this positron emission tomography (PET) study with [11 C]UCB-J, we evaluated synaptic vesicle glycoprotein 2A (SV2A) binding, which is decreased in resected brain tissues from epilepsy patients, in subjects with temporal lobe epilepsy (TLE) and compared the regional binding pattern to [18 F]fluorodeoxyglucose (FDG) uptake. METHODS Twelve TLE subjects and 12 control subjects were examined. Regional [11 C]UCB-J binding potential (BPND ) values were estimated using the centrum semiovale as a reference region. [18 F]FDG uptake in TLE subjects was quantified using mean radioactivity values. Asymmetry in outcome measures was assessed by comparison of ipsilateral and contralateral regions. Partial volume correction (PVC) with the iterative Yang algorithm was applied based on the FreeSurfer segmentation. RESULTS In 11 TLE subjects with medial temporal lobe sclerosis (MTS), the hippocampal volumetric asymmetry was 25 ± 11%. After PVC, [11 C]UCB-J BPND asymmetry indices were 37 ± 19% in the hippocampus, with very limited asymmetry in other brain regions. Reductions in [11 C]UCB-J BPND values were restricted to the sclerotic hippocampus when compared to control subjects. The corresponding asymmetry in hippocampal [18 F]FDG uptake was 22 ± 7% and correlated with that of [11 C]UCB-J BPND across subjects (R2 = .38). Hippocampal asymmetries in [11 C]UCB-J binding were 1.7-fold larger than those of [18 F]FDG uptake. SIGNIFICANCE [11 C]UCB-J binding is reduced in the seizure onset zone of TLE subjects with MTS. PET imaging of SV2A may be a promising biomarker approach in the presurgical selection and evaluation of TLE patients and may improve the sensitivity of molecular imaging for seizure focus detection.
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Affiliation(s)
- Sjoerd J Finnema
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Takuya Toyonaga
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Kamil Detyniecki
- Department of Neurology, Yale University, New Haven, Connecticut, USA
| | - Ming-Kai Chen
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Mark Dias
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Qianyu Wang
- Department of Neurology, Yale University, New Haven, Connecticut, USA
| | - Shu-Fei Lin
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Mika Naganawa
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Jean-Dominique Gallezot
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Yihuan Lu
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Nabeel B Nabulsi
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Yiyun Huang
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA
| | - Dennis D Spencer
- Department of Neurosurgery, Yale University, New Haven, Connecticut, USA
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, PET Center, Yale University, New Haven, Connecticut, USA.,Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA
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Andrews JP, Ammanuel S, Kleen J, Khambhati AN, Knowlton R, Chang EF. Early seizure spread and epilepsy surgery: A systematic review. Epilepsia 2020; 61:2163-2172. [PMID: 32944952 DOI: 10.1111/epi.16668] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 08/03/2020] [Accepted: 08/04/2020] [Indexed: 01/03/2023]
Abstract
OBJECTIVE A fundamental question in epilepsy surgery is how to delineate the margins of cortex that must be resected to result in seizure freedom. Whether and which areas showing seizure activity early in ictus must be removed to avoid postoperative recurrence of seizures is an area of ongoing research. Seizure spread dynamics in the initial seconds of ictus are often correlated with postoperative outcome; there is neither a consensus definition of early spread nor a concise summary of the existing literature linking seizure spread to postsurgical seizure outcomes. The present study is intended to summarize the literature that links seizure spread to postoperative seizure outcome and to provide a framework for quantitative assessment of early seizure spread. METHODS A systematic review was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A Medline search identified clinical studies reporting data on seizure spread measured by intracranial electrodes, having at least 10 subjects and reporting at least 1-year postoperative outcome in the English literature from 1990 to 2019. Studies were evaluated regarding support for a primary hypothesis: Areas of early seizure spread represent cortex with seizure-generating potential. RESULTS The search yielded 4562 studies: 15 studies met inclusion criteria and 7 studies supported the primary hypothesis. The methods and metrics used to describe seizure spread were heterogenous. The timeframe of seizure spread associated with seizure outcome ranged from 1-14 seconds, with large, well-designed, retrospective studies pointing to 3-10 seconds as most likely to provide meaningful correlates of postoperative seizure freedom. SIGNIFICANCE The complex correlation between electrophysiologic seizure spread and the potential for seizure generation needs further elucidation. Prospective cohort studies or trials are needed to evaluate epilepsy surgery targeting cortex involved in the first 3-10 seconds of ictus.
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Affiliation(s)
- John P Andrews
- Department of Neurological Surgery, School of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Simon Ammanuel
- Department of Neurological Surgery, School of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Jonathan Kleen
- Department of Neurology, School of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, School of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Robert Knowlton
- Department of Neurology, School of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Edward F Chang
- Department of Neurological Surgery, School of Medicine, University of California-San Francisco, San Francisco, California, USA
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Kananen J, Helakari H, Korhonen V, Huotari N, Järvelä M, Raitamaa L, Raatikainen V, Rajna Z, Tuovinen T, Nedergaard M, Jacobs J, LeVan P, Ansakorpi H, Kiviniemi V. Respiratory-related brain pulsations are increased in epilepsy-a two-centre functional MRI study. Brain Commun 2020; 2:fcaa076. [PMID: 32954328 PMCID: PMC7472909 DOI: 10.1093/braincomms/fcaa076] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/29/2020] [Accepted: 05/05/2020] [Indexed: 01/03/2023] Open
Abstract
Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n = 102) and patients with epilepsy (n = 33) and furthermore to drug-naive seizure patients (n = 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11-0.51 Hz) were significantly (P < 0.05) increased in patients with epilepsy, with an increase in both signal variance and power. At the individual level, over 80% of medicated and drug-naive seizure patients exhibited areas of abnormal brain signal power that correlated well with the known clinical diagnosis, while none of the controls showed signs of abnormality with the same threshold. The differences were most apparent in the basal brain structures, respiratory centres of brain stem, midbrain and temporal lobes. Notably, full-band, very low frequency (0.01-0.1 Hz) and cardiovascular (0.8-1.76 Hz) brain pulses showed no differences between groups. This study extends and confirms our previous results of abnormal fast functional MRI signal variance in epilepsy patients. Only respiratory-related brain pulsations were clearly increased with no changes in either physiological cardiorespiratory rates or head motion between the subjects. The regional alterations in brain pulsations suggest that mechanisms driving the cerebrospinal fluid homeostasis may be altered in epilepsy. Magnetic resonance encephalography has both increased sensitivity and high specificity for detecting the increased brain pulsations, particularly in times when other tools for locating epileptogenic areas remain inconclusive.
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Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Zalan Rajna
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu 90014, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY 14642, USA
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu 90220, Finland
- Research Unit of Neuroscience, Neurology, University of Oulu, Oulu 90220, Finland
- Department of Neurology, Oulu University Hospital, Oulu 90029, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
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48
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Abstract
Temporal lobe epilepsy (TLE) is the most common type of drug-resistant focal epilepsy. Epilepsy can be conceptualized as a network disorder with the epileptogenic zone a critical node of the network. Temporal lobe networks can be identified on the microscale and macroscale, both during the interictal and ictal periods. This review summarizes the current understanding of TLE networks as studied by neurophysiological and imaging techniques discussing both functional and structural connectivity.
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49
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Fischer GM, Vaziri Fard E, Shah MN, Patel RP, Von Allmen G, Ballester LY, Bhattacharjee MB. Filamin A-negative hyaline astrocytic inclusions in pediatric patients with intractable epilepsy: report of 2 cases. J Neurosurg Pediatr 2020; 26:38-44. [PMID: 32217802 DOI: 10.3171/2020.1.peds19706] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 01/27/2020] [Indexed: 11/06/2022]
Abstract
Although rare, hyaline cytoplasmic inclusions isolated to astrocytes of the cerebral cortex have been identified in a spectrum of diseases ranging from intractable epilepsy in pediatric patients with only mild to moderate developmental delays to Aicardi syndrome. These inclusions classically stain positive for filamin A, giving rise to the term "filaminopathies." The authors report on 2 pediatric patients with intractable epilepsy and developmental delay who uniquely displayed filamin A-negative hyaline astrocytic inclusions in resected brain tissues. Additionally, these inclusions stained positive for S100 and negative for glial fibrillary acidic protein, chromogranin, neurofilament, CD34, vimentin, periodic acid-Schiff (PAS), and Alcian blue. These are the first reported cases of filamin A-negative hyaline astrocytic inclusions, providing a novel variation on a previously reported entity and justification to further investigate the pathogenesis of these inclusions. The authors compare their findings with previously reported cases and review the literature on hyaline astrocytic inclusions in intractable pediatric epilepsy.
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Affiliation(s)
| | | | - Manish N Shah
- 2Neurosurgery.,5Memorial Hermann Hospital-Texas Medical Center, Houston, Texas
| | - Rajan P Patel
- 3Diagnostic and Interventional Imaging, and.,5Memorial Hermann Hospital-Texas Medical Center, Houston, Texas
| | - Gretchen Von Allmen
- 4Pediatrics, The University of Texas Health Science Center at Houston; and.,5Memorial Hermann Hospital-Texas Medical Center, Houston, Texas
| | - Leomar Y Ballester
- Departments of1Pathology and Laboratory Medicine.,2Neurosurgery.,5Memorial Hermann Hospital-Texas Medical Center, Houston, Texas
| | - Meenakshi B Bhattacharjee
- Departments of1Pathology and Laboratory Medicine.,5Memorial Hermann Hospital-Texas Medical Center, Houston, Texas
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50
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Ammanuel SG, Kleen JK, Leonard MK, Chang EF. Interictal Epileptiform Discharges and the Quality of Human Intracranial Neurophysiology Data. Front Hum Neurosci 2020; 14:44. [PMID: 32194384 PMCID: PMC7062638 DOI: 10.3389/fnhum.2020.00044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 01/31/2020] [Indexed: 12/25/2022] Open
Abstract
Intracranial electroencephalography (IEEG) involves recording from electrodes placed directly onto the cortical surface or deep brain locations. It is performed on patients with medically refractory epilepsy, undergoing pre-surgical seizure localization. IEEG recordings, combined with advancements in computational capacity and analysis tools, have accelerated cognitive neuroscience. This Perspective describes a potential pitfall latent in many of these recordings by virtue of the subject population—namely interictal epileptiform discharges (IEDs), which can cause spurious results due to the contamination of normal neurophysiological signals by pathological waveforms related to epilepsy. We first discuss the nature of IED hazards, and why they deserve the attention of neurophysiology researchers. We then describe four general strategies used when handling IEDs (manual identification, automated identification, manual-automated hybrids, and ignoring by leaving them in the data), and discuss their pros, cons, and contextual factors. Finally, we describe current practices of human neurophysiology researchers worldwide based on a cross-sectional literature review and a voluntary survey. We put these results in the context of the listed strategies and make suggestions on improving awareness and clarity of reporting to enrich both data quality and communication in the field.
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Affiliation(s)
- Simon G Ammanuel
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Jonathan K Kleen
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Matthew K Leonard
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
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